Characteristic determination method, device, program, and system

Abstract

A reception unit (32) receives a request for a determination regarding characteristics of a subject. An acquisition unit (34) acquires measurement data pertaining to the amount of an analyte in a sample collected from the subject and stores the acquired measurement data in a measurement data DB (40). A determination unit (36) uses the measurement data stored in the measurement data DB (40) to make a determination regarding the characteristics and outputs the result of the determination. If measurement data has been stored in the measurement data DB (40) in response to a request for a determination regarding characteristics of a subject received at a first time point, and another such request is received with respect to the same subject at a second time point later in time than the first time point, the determination unit (36) makes a determination regarding the characteristics using the measurement data at the first time point stored in the measurement data DB (40).

Description

Property determination method, device, program, and system

[0001] The present disclosure relates to a property determination method, a property determination device, a property determination program, and a property determination system.

[0002] A service is provided to test for breast cancer recurrence by measuring the expression levels of 21 genes using specimens (cells) from subjects to clarify the biological characteristics of each individual's tumor. With this service, medical institutions send specimens to laboratories, which then perform genetic analysis and other procedures based on the specimens to obtain results (recurrence scores) and report these results to medical institutions.

[0003] In addition, a testing service is being offered that uses test subjects' samples (blood or tissue) to simultaneously detect and analyze mutations in 324 cancer-related genes and perform companion diagnostics. In this service, similar to the above service, the medical institution sends the sample to a testing laboratory, which then performs genetic analysis based on the sample, obtains the results, and reports the results to the medical institution.

[0004] Also proposed is a disease prevalence determination device that includes a sample data acquisition unit that acquires sample data including the expression levels of multiple types of miRNA in a biological sample, and a prevalence determination unit that outputs prevalence determination results for multiple diseases in multiple body parts for the acquired sample data using a trained model that can determine the prevalence of each of multiple diseases, including multiple malignant diseases or multiple benign diseases, including cases where the patient is affected by multiple diseases, obtained in advance by performing machine learning using training data including multiple sample data having items for identifying the presence or absence of multiple diseases in multiple body parts.

[0005] Patent No. 7021097

[0006] Oncotype DX Breast Cancer Recurrence Score Program [online], [search date 2024.05.01], Internet <URL: https: / / www.oncotypeiq.com / ja-jp / breast-cancer / healthcare-professionals / oncotype-dx-breast-recurrence-score / how-to-order-a-test#> FoundationOne Liquid CDx Cancer Genomic Profile [online], [Retrieved May 1, 2024], Internet<URL: https: / / www.hos.akita-u.ac.jp / departmentlist / file / genome_diagnosis / document_20211101.pdf>

[0007] In the above-mentioned conventional technology services, it is necessary to obtain a new specimen for testing for a disease that was not requested at the time of specimen acquisition or for testing for a new disease that has been identified after specimen acquisition. Also, there are cases where a user wants to know the test results of specimens obtained in the past for the disease tested for in the specimen currently acquired, but if a test for that disease has not been requested in the past, the past test results cannot be known.

[0008] The present disclosure has been made in consideration of the above points, and aims to provide a property determination device, method, program, and system that can flexibly respond to requests for determining the properties of a subject from the second time onwards for the same subject.

[0009] To achieve the above object, the property determination method according to the present disclosure is a property determination method in which a computer executes a process including accepting a request for determination of the property of a subject, acquiring measurement data on the amount of a substance to be measured in a sample provided by the subject, storing the acquired measurement data in a memory unit, making a determination of the property using the measurement data stored in the memory unit, and outputting a determination result, in which, when a request for determination of the property of the same subject is received at a second time point later than the first time point, while the measurement data corresponding to the request accepted at a first time point is stored in the memory unit, the determination of the property is made using the measurement data at the first time point stored in the memory unit. This allows for flexible response to subsequent requests for determination of the property of the same subject.

[0010] Furthermore, at the first time point, a request for determination of a first property may be accepted, and the measurement data may be acquired and stored in the storage unit, and at the second time point, a request for determination of a second property may be accepted, and the measurement data at the first time point stored in the storage unit may be used to make a determination of the second property. In this way, even if a request is made at the second time point for a property different from that requested at the first time point, by using the measurement data at the first time point, it is possible to make a determination at the second time point without providing a sample again.

[0011] Furthermore, the measurement data acquired at the first time point may be associated with time information indicating the first time point and stored in the storage unit, a request for determination regarding the property may be accepted at the second time point, and the measurement data acquired at the second time point may be associated with time information indicating the second time point and stored in the storage unit, and determination regarding the property at the first time point and the second time point may be made using the measurement data at the first time point and the measurement data at the second time point stored in the storage unit. This makes it possible to determine, at the second time point, the transition of the property, including the first time point, for a property not requested at the first time point.

[0012] The measurement data may be the expression levels of each of a plurality of small RNAs, thereby enabling determination of a plurality of properties using measurement data obtained from a single sample.

[0013] The process of acquiring the measurement data may be performed using a next-generation sequencer, thereby enabling efficient acquisition of the measurement data.

[0014] Furthermore, the process of determining the properties may be performed using a machine learning model that has been trained in advance to determine the correspondence between measurement data and determination results.

[0015] In addition, the property determination device of the present disclosure includes a reception unit that receives a request for determination regarding the property of a subject, an acquisition unit that acquires measurement data regarding the amount of a substance to be measured in a sample provided by the subject and stores the acquired measurement data in a memory unit, and a determination unit that makes a determination regarding the property using the measurement data stored in the memory unit and outputs a determination result, in which when the reception unit receives a request for determination regarding the property for the same subject at a second time point that is later in time than the first time point, when the measurement data corresponding to the request received at the first time point is stored in the memory unit, the determination unit makes a determination regarding the property using the measurement data at the first time point stored in the memory unit.

[0016] In addition, the property determination program of the present disclosure is a property determination program that causes a computer to function as a reception unit that receives a request for determination regarding the property of a subject, an acquisition unit that acquires measurement data regarding the amount of a substance to be measured in a sample provided by the subject and stores the acquired measurement data in a memory unit, and a determination unit that makes a determination regarding the property using the measurement data stored in the memory unit and outputs a determination result, wherein when the reception unit receives a request for determination regarding the property for the same subject at a second time point that is later in time than the first time point, when the measurement data corresponding to the request received at the first time point is stored in the memory unit, the determination unit makes a determination regarding the property using the measurement data at the first time point stored in the memory unit.

[0017] Furthermore, the property determination system according to the present disclosure includes a reception unit that receives a request for determination regarding the property of a subject, an acquisition unit that acquires measurement data regarding the amount of a substance to be measured in a sample provided by the subject, a memory unit that stores the acquired measurement data, and a determination unit that makes a determination regarding the property using the measurement data stored in the memory unit and outputs a determination result, in which, when the reception unit receives a request for determination regarding the property for the same subject at a second time point that is later in time than the first time point, when the measurement data corresponding to the request received at the first time point is stored in the memory unit, the determination unit makes a determination regarding the property using the measurement data at the first time point stored in the memory unit.

[0018] According to the property determination device, method, program, and system disclosed herein, it is possible to flexibly respond to requests for determining the property of a subject from the second time onwards for the same subject.

[0019] 1 is a diagram showing a schematic configuration of a property determination system; 2 is a block diagram showing a hardware configuration of a property determination device; 3 is a block diagram showing an example of a functional configuration of a property determination device; 4 is a diagram showing an example of a measurement data DB; 5 is a flowchart showing the flow of a property determination process; 6 is a diagram for explaining a specific example of an aspect to which the present embodiment is applied; 7 is a diagram for explaining a specific example of an aspect to which the present embodiment is applied;

[0020] An example of an embodiment of the technology of the present disclosure will be described below with reference to the drawings. Note that components and processes that perform the same operations, actions, and functions are given the same reference numerals throughout the drawings, and redundant explanations may be omitted as appropriate. Each drawing is merely a schematic illustration to allow a sufficient understanding of the technology of the present disclosure. Therefore, the technology of the present disclosure is not limited to the illustrated examples. Furthermore, in this embodiment, explanations of configurations that are not directly related to the present disclosure or well-known configurations may be omitted.

[0021] In this embodiment, as an example, a property determination system for determining whether or not a subject has a specific disease based on the expression level of small RNA measured from a specimen of the subject will be described. The expression level of small RNA is an example of the "abundance of a substance to be measured" in the present disclosure, and the presence or absence of a specific disease is an example of the "property of the subject" in the present disclosure.

[0022] 1 shows a schematic configuration of a property determination system 100 according to this embodiment. The property determination system 100 includes a property determination device 10, a user terminal 50, and a measurement device 60.

[0023] The user terminal 50 is an information processing device such as a personal computer, tablet terminal, smartphone, or the like used by a medical institution staff member such as a doctor, a subject, or a user who uses the services provided by the property determination system 100. The user terminal 50 transmits a determination request input by the user to the property determination device 10. The determination request is information for requesting a determination regarding the subject's property, and includes the subject's identification information (hereinafter referred to as "subject ID"), the property to be determined, and information on whether past measurement data can be used. In this embodiment, the property to be determined is the type of disease.

[0024] The information on whether past measurement data can be used indicates whether measurement data measured in response to a past determination request can be used to determine whether or not a patient is affected by a disease. There are three patterns for the information on whether past measurement data can be used: (i) only past measurement data is used, (ii) past measurement data and current measurement data are used, and (iii) past measurement data is not used (only current measurement data is used).

[0025] The measuring device 60 is placed, for example, at a facility of a service provider that provides services using the property determination system 100. Note that the measuring device 60 may also be placed at a facility of an external provider different from the service provider. The measuring device 60 measures the expression level of small RNA in a sample collected from a subject. Identification information for the determination request (hereinafter referred to as a "request ID") is assigned to the sample. The request ID may be a number assigned to each determination request, or may be a combination of the subject ID and the request date, etc.

[0026] Examples of specimens collected from subjects include body fluids, cells, extracellular vesicles, tissue fragments, etc. Examples of body fluids include blood, serum, plasma, urine, tears, saliva, sweat, semen, lymph, tissue fluid, body cavity fluid (e.g., pleural effusion, ascites, etc.), cerebrospinal fluid, amniotic fluid, vaginal fluid, nasal mucus, etc. Examples of cells include red blood cells, white blood cells, platelets, etc. Examples of extracellular vesicles include exosomes, liposomes, etc. Examples of tissue fragments include FFPE (Formalin Fixed Paraffin Embedded) specimens, biopsy specimens, frozen specimens, etc. Note that the specimen may be a specimen from which multiple small RNAs are derived, in other words, a specimen from which the expression levels of multiple small RNAs can be measured.

[0027] The subject may be a human or a non-human animal, including non-human mammals (monkeys, dogs, cats, mice, rats, rabbits, cows, horses, pigs, sheep, etc.), birds (chickens, quails, etc.), etc.

[0028] Examples of small RNAs include microRNAs. Note that the small RNA may be small RNAs other than microRNAs (e.g., piRNAs, tsRNAs, etc.).

[0029] The measurement device 60 may be, for example, a next-generation sequencer (NGS). In this case, the measurement device 60 measures multiple small RNAs contained in the subject's body fluid and identifies the base sequence of each small RNA. The measurement device 60 counts the number of each identified small RNA for each base sequence and calculates the number of reads of the small RNA. This number of reads of the small RNA represents the expression level of the small RNA, specifically, the absolute expression level. The measurement device 60 outputs this number of reads of the small RNA as measurement data representing the result of measuring the expression levels of multiple small RNAs in the subject's body fluid.

[0030] However, while the expression levels of multiple small RNAs (e.g., microRNAs) in bodily fluids (e.g., blood) are absolute values ​​derived from the living body, it is difficult to quantify the expression levels of small RNAs in bodily fluids as absolute values ​​because the expression levels must be quantified using the measurement device 60 or reagent processing. Therefore, the measurement results from NGS may be processed to obtain relative values ​​of the expression levels of small RNAs (hereinafter referred to as "relative expression levels") as measurement data. Specifically, the number of reads of small RNAs output by NGS may be normalized to obtain relative expression levels. Examples of normalization methods include RPM (reads per million) normalization and normalization using an internal standard small RNA. The measurement data may also be absolute quantitative values ​​quantified as absolute values.

[0031] The data processing of the measurement results as described above may be performed within the measurement device 60, or may be performed by an information processing device separate from the measurement device 60. The separate information processing device may be the property determination device 10 described below.

[0032] The measuring device 60 assigns the request ID assigned to the sample to the measurement data and outputs it to the property determination device 10. The measurement data may be, for example, a BAM file. Note that if the information regarding whether past measurement data can be used in the determination request is the above-mentioned "(i) Use only past measurement data," there is no need to collect a sample or measure small RNA in response to the current determination request, so no measurement data is output from the measuring device 60, and only the determination request from the user terminal 50 is output to the property determination device 10.

[0033] As the measurement device 60, in addition to a next-generation sequencer, a DNA chip, a quantitative PCR, a flow cytometer, etc. can also be used as long as it can measure the expression levels of multiple small RNAs.

[0034] Fig. 2 is a block diagram showing the hardware configuration of the property determination device 10 according to this embodiment. As shown in Fig. 2, the property determination device 10 includes a CPU (Central Processing Unit) 12, a memory 14, a storage device 16, an input device 18, an output device 20, a storage medium reader 22, and a communication I / F (Interface) 24. Each component is connected to each other via a bus 26 so as to be able to communicate with each other.

[0035] The storage device 16 stores a property determination program for executing the property determination process described below. The CPU 12 is a central processing unit that executes various programs and controls each component. That is, the CPU 12 reads the program from the storage device 16 and executes the program using the memory 14 as a work area. The CPU 12 controls each component and performs various arithmetic processes in accordance with the program stored in the storage device 16.

[0036] The memory 14 is configured with RAM (Random Access Memory) and serves as a working area for temporarily storing programs and data. The storage device 16 is configured with ROM (Read Only Memory), HDD (Hard Disk Drive), SSD (Solid State Drive), etc., and stores various programs including the operating system and various data.

[0037] The input device 18 is a device for performing various inputs, such as a keyboard or a mouse. The output device 20 is a device for outputting various information, such as a display or a printer. A touch panel display may be used as the output device 20 to function as the input device 18.

[0038] The storage medium reader 22 reads data stored in various storage media such as CD (Compact Disc)-ROM, DVD (Digital Versatile Disc)-ROM, Blu-ray Disc, USB (Universal Serial Bus) memory, etc., and writes data to the storage media. The communication I / F 24 is an interface for communicating with other devices, and uses standards such as Ethernet (registered trademark), FDDI, or Wi-Fi (registered trademark).

[0039] Next, the functional configuration of the property determination device 10 according to this embodiment will be described. Fig. 3 is a block diagram showing an example of the functional configuration of the property determination device 10. As shown in Fig. 3, the property determination device 10 includes, as its functional configuration, a reception unit 32, an acquisition unit 34, and a determination unit 36. A measurement data DB (Database) 40 and a determination model 42 are stored in a predetermined storage area of ​​the property determination device 10. Each functional configuration is realized when the CPU 12 reads out a property determination program stored in the storage device 16, expands it into the memory 14, and executes it.

[0040] The reception unit 32 receives a determination request transmitted from the user terminal 50. The reception unit 32 passes the received determination request to the acquisition unit 34 and the determination unit 36.

[0041] The acquiring unit 34 acquires the measurement data output from the measuring device 60. If the measurement data output from the measuring device 60 has undergone data processing such as the normalization described above, the acquiring unit 34 acquires the measurement data after the data processing. The acquiring unit 34 associates the measurement data with a subject ID and a measurement date, stores the measurement data in a measurement data DB 40 such as that shown in FIG. 4, and passes the measurement data to the determining unit 36. The subject ID and measurement date are identified by comparing a request ID assigned to the measurement data with the determination request. The subject ID and measurement date may be assigned to the measurement data by the measuring device 60.

[0042] The determination unit 36 ​​uses the measurement data stored in the measurement data DB 40 to make a determination regarding the property and outputs the determination result.

[0043] Specifically, the determination unit 36 ​​acquires the measurement data to be used for the determination from the measurement data DB 40 based on whether the past measurement data is usable or not, which is included in the determination request passed from the reception unit 32. More specifically, when the information on whether the past measurement data is usable or not indicates that the past measurement data is to be used, the determination unit 36 ​​acquires the past measurement data stored in the measurement data DB 40 in association with the subject ID included in the determination request. When there are multiple pieces of past measurement data, all of the past measurement data may be acquired, or the determination request may include a specification of which point in time the measurement data is to be used, and the past measurement data corresponding to this specification may be acquired.

[0044] Furthermore, the determination unit 36 ​​inputs the acquired measurement data into a determination model 42 to obtain a determination result.

[0045] The determination model 42 may be a machine learning model that has been trained in advance to determine the correspondence between measurement data and determination results. Specifically, the determination model 42 is trained for each type of disease using, as training data, expression level data for a predetermined number of small RNAs selected according to the type of disease from expression level data for multiple small RNAs measured from samples of subjects whose disease presence or absence is known. For example, if the small RNAs are microRNAs, the determination model 42 for each type of disease is trained selectively using expression level data for approximately 150 types of microRNAs for each disease out of 2,600 types of microRNAs.

[0046] Therefore, the determination unit 36 ​​inputs data on the expression levels of small RNAs selected from the acquired measurement data according to the type of disease indicated by the type of determination included in the determination request into a determination model 42 for that type of disease. As a result, the determination model 42 outputs the presence or absence of the disease to be determined. The determination unit 36 ​​outputs the output of the determination model 42 as the determination result. For example, if the small RNA is a microRNA, data on the expression levels of approximately 150 types of microRNAs corresponding to the disease to be determined is selectively used from 2,600 types of microRNAs according to the disease to be determined, as in the training of the determination model 42 described above, and a determination is made using the determination model 42 corresponding to the type of disease to be determined. As a result, it is possible to determine multiple properties (here, diseases) using measurement data obtained from a sample collected once.

[0047] Next, the operation of the property determination system 100 according to this embodiment will be described.

[0048] A determination request is sent from the user terminal 50 to the property determination device 10, and, if necessary, a sample collected from the subject is sent to a service provider that provides services using the property determination system 100. When the sample is sent to the service provider, the service provider measures the expression level of small RNA in the sample using the measurement device 60. When the determination request is input to the property determination device 10, the property determination device 10 executes the property determination process.

[0049] Fig. 5 is a flowchart showing the flow of the property determination process executed by the CPU 12 of the property determination device 10. The CPU 12 reads out the property determination program from the storage device 16, loads it into the memory 14, and executes it, causing the CPU 12 to function as each functional component of the property determination device 10 and execute the property determination process shown in Fig. 5. The property determination process is an example of the "property determination method" of the present disclosure.

[0050] In step S10, the reception unit 32 receives a determination request input to the property determination device 10 and passes the received determination request to the acquisition unit 34 and the determination unit 36. Next, in step S12, the determination unit 36 ​​determines whether or not there is measurement data measured in response to the current determination request, based on whether or not past measurement data included in the determination request is available. If there is current measurement data, the process proceeds to step S14. If there is no current measurement data, i.e., if only past measurement data is to be used, the process proceeds to step S16.

[0051] In step S14, the acquisition unit 34 acquires the measurement data output from the measurement device 60, associates the measurement data with the subject ID and the measurement date, stores the measurement data in the measurement data DB 40, and passes it to the determination unit 36.

[0052] Next, in step S16, the determination unit 36 ​​determines whether or not to use the past measurement data based on whether or not the past measurement data included in the determination request can be used. If the past measurement data is to be used, the process proceeds to step S18, and if the past measurement data is not to be used, the process proceeds to step S20.

[0053] In step S18, the determination unit 36 ​​acquires past measurement data stored in the measurement data DB 40 in association with the subject ID included in the determination request. Next, in step S20, the determination unit 36 ​​inputs data on the expression levels of small RNAs selected from the acquired measurement data according to the type of disease to be determined included in the determination request into the determination model 42 for that type of disease. As a result, the determination model 42 outputs the presence or absence of the disease to be determined. Then, the determination unit 36 ​​outputs the output of the determination model 42 as the determination result, and the property determination process ends.

[0054] By executing the property determination process as described above, when a determination request is received at a second time point later than the first time point, with the measurement data corresponding to the determination request received at a first time point stored in the measurement data DB 40, a determination regarding the property is made using the measurement data at the first time point stored in the measurement data DB 40. More specific aspects will be described in the following two examples.

[0055] In the first aspect, at a first time point, a request for a determination regarding a first property is accepted, and measurement data is acquired and stored in the measurement data DB 40. Then, at a second time point, a request for a determination regarding a second property is accepted, and in response to the determination request regarding the first property, a determination regarding the second property is made using the measurement data at the first time point stored in the measurement data DB 40.

[0056] A specific example of the first aspect will be described with reference to Figure 6. As shown in Figure 6, a request for determining whether or not a subject has disease X is made at time T1, and a sample collected from the subject is provided. Then, data on the expression levels of small RNAs in the provided sample is measured by the measurement device 60 and stored in the measurement data DB 40. The determination unit 36 ​​uses the measurement data to determine whether or not the subject has disease X and outputs the determination result. Then, at time T2, some time after time T1, the same subject requests a determination for whether or not the subject has disease Y. In this case, the presence or absence of disease Y can be determined and the determination result can be output using the measurement data stored in the measurement data DB 40 at time T1, without collecting a sample from the subject.

[0057] In the second aspect, measurement data acquired at a first time point is associated with time information indicating the first time point and stored in the measurement data DB 40, and a determination request is accepted at a second time point, and the measurement data acquired at the second time point is associated with time information indicating the second time point and stored in the measurement data DB 40. Then, the measurement data at the first time point and the measurement data at the second time point stored in the measurement data DB 40 are used to perform determinations regarding properties at the first time point and the second time point.

[0058] A specific example of the second aspect will be described with reference to FIG. 7 . As shown in FIG. 7 , a sample is collected from a certain subject at time T1, similar to time T1 in the example of FIG. 6 , and the presence or absence of disease X is determined. Then, at time T2, after some time has passed since time T1, a new disease Z that was not included in the diseases to be determined at time T1 is added to the list of diseases to be determined. In this case, a request for determining the progression of the presence or absence of disease Z is made at time T2 for the same subject, and a sample collected from the subject is provided. Then, data on the expression levels of small RNAs in the provided sample is measured by the measuring device 60, and the current measurement data is obtained. Past measurement data stored in the measurement data DB 40 at time T1 is also obtained. Then, by determining the presence or absence of disease Z for each of the past measurement data and the current measurement data, the progression of the presence or absence of disease Z between time T1 and time T2 can be determined. In this way, the progression of the presence or absence of disease Z can be determined at time T2, even though a request for determination of disease Z was not made at time T1. Furthermore, even if the request for judgment at time T2 is not a request for judgment about the ``progression'' of whether or not the patient has disease Z, but a request for judgment about whether or not the patient has disease Z, a judgment result based on the measurement data at time T1 can be provided in response to the judgment request at time T2.

[0059] In the example of FIG. 7 , the measurement data acquired at time T2 may or may not be stored in the measurement data DB 40. When measurement data at multiple time points is stored in the measurement data DB 40, it is possible to determine the transition of properties at multiple time points. Furthermore, the determination flow at time T1 in FIG. 6 is a determination using only the current measurement data, and the determination flow at time T2 in FIG. 6 is a determination using only the past measurement data. Furthermore, the determination flow at time T2 in FIG. 7 is a determination using both the past measurement data and the current measurement data. Furthermore, the manner in which this embodiment is applied is not limited to the above two examples.

[0060] As described above, according to the property determination system of this embodiment, the property determination device accepts a request for determination of a property of a subject. The property determination device then acquires measurement data regarding the expression levels of small RNAs in a sample provided by the subject, stores the acquired measurement data in a measurement data DB, and uses the measurement data to determine the property and output the determination result. When the property determination device accepts a determination request for the same subject at a second time point later than the first time point, while the measurement data corresponding to the determination request accepted at the first time point is stored in the measurement data DB, the property determination device uses the measurement data stored at the first time point to make a determination of the property. This allows the device to flexibly respond to subsequent determination requests for the same subject, such as by using past measurement data to determine a property different from that at the time of the previous determination request, or by determining the progress of a property for which a determination request has not been accepted in the past, including past time points.

[0061] The processing flow of the program described in the above embodiment is an example, and unnecessary steps may be deleted, new steps may be added, or the processing order may be changed within the scope of the main idea.

[0062] For example, when the judgment model 42 is updated, past measurement data stored in the measurement data DB 40 may be input into the updated judgment model 42, and judgment results may be obtained for the past measurement data using the updated judgment model 42.

[0063] In the above embodiment, the case of determining whether or not a subject has a specific disease has been described as an example of the subject's characteristics, but the present invention is not limited to this. For example, the characteristics to be determined may be confirmation of the efficacy of a drug administered to the subject, determination of the possibility of disease recurrence, determination of lifestyle habits such as whether or not the subject has a smoking or drinking history, prediction of physical age, etc.

[0064] In the above embodiment, the expression level of small RNA is measured as an example of the amount of a substance to be measured, but the present invention is not limited to this. The amount of other substances, such as proteins, that can be measured in a sample collected from a subject may also be measured.

[0065] In the above embodiment, the case where the determination request includes information on whether or not past measurement data can be used has been described, but the present invention is not limited to this. The determination on whether or not past measurement data can be used may be made based on the object of determination, whether or not current measurement data has been acquired, whether or not past measurement data is stored in the measurement data DB, etc.

[0066] In the above embodiment, the measurement device and the property determination device are configured as separate devices, but they may be configured as the same device. Furthermore, the functional units and databases of the property determination device may be distributed and located in different devices. For example, the measurement data DB may be stored in an external device separate from the property determination device.

[0067] In addition, the property determination process executed by the CPU after reading the software (program) in the above embodiment may be executed by various processors other than the CPU. Examples of such processors include programmable logic devices (PLDs) (such as field-programmable gate arrays (FPGAs)) whose circuit configuration can be changed after manufacture, and dedicated electrical circuits such as application-specific integrated circuits (ASICs) that are processors with circuit configurations specifically designed to execute specific processes. The property determination process may be executed by one of these various processors, or by a combination of two or more processors of the same or different types (e.g., multiple FPGAs, or a combination of a CPU and an FPGA). The hardware structure of these various processors is, more specifically, an electrical circuit that combines circuit elements such as semiconductor devices.

[0068] In the above embodiment, the property determination program is pre-stored (installed) in a storage device, but the present invention is not limited to this. The program may be provided in a form recorded on a recording medium such as a CD-ROM, a DVD-ROM (Digital Versatile Disc Read Only Memory), or a USB (Universal Serial Bus) memory. The program may also be downloaded from an external device via a network.

[0069] The following are additional notes regarding this disclosure.

[0070] (Supplementary Item 1) A property determination method in which a computer executes processes including accepting a request for a determination regarding the property of a subject, acquiring measurement data regarding the amount of a substance to be measured in a sample provided by the subject, storing the acquired measurement data in a memory unit, making a determination regarding the property using the measurement data stored in the memory unit, and outputting a determination result, wherein when a request for a determination regarding the property is received for the same subject at a second time point that is later in time than the first time point, with the measurement data corresponding to the request accepted at the first time point stored in the memory unit, the determination regarding the property is made using the measurement data at the first time point stored in the memory unit.

[0071] (Supplementary Item 2) A property determination method according to Supplementary Item 1, comprising: at the first point in time, accepting a request for determination regarding a first property and acquiring and storing the measurement data in the memory unit; at the second point in time, accepting a request for determination regarding a second property; and making a determination regarding the second property using the measurement data at the first point in time stored in the memory unit.

[0072] (Supplementary Item 3) A property determination method according to Supplementary Item 1 or Supplementary Item 2, comprising: storing the measurement data acquired at the first time point in the memory unit in association with time information indicating the first time point; accepting a request for determination regarding the property at the second time point, and storing the measurement data acquired at the second time point in the memory unit in association with time information indicating the second time point; making a determination regarding the property at the first time point and the second time point using the measurement data at the first time point and the measurement data at the second time point stored in the memory unit, and outputting a determination result.

[0073] (Supplementary Item 4) The property determination method according to any one of Supplementary Items 1 to 3, wherein the measurement data is the expression level of each of a plurality of small RNAs.

[0074] (Supplementary Item 5) The property determination method according to Supplementary Item 4, wherein the process of acquiring the measurement data is performed using a next-generation sequencer.

[0075] (Supplementary Item 6) The property determination method according to any one of Supplementary Items 1 to 5, wherein the process of determining the property is performed using a machine learning model that has been trained in advance to determine the correspondence between measurement data and determination results.

[0076] REFERENCE SIGNS LIST 10 Property determination device 12 CPU 14 Memory 16 Storage device 18 Input device 20 Output device 22 Storage medium reading device 24 Communication I / F 26 Bus 32 Reception unit 34 Acquisition unit 36 ​​Determination unit 40 Measurement data DB 42 Determination model 50 User terminal 60 Measurement device 100 Property determination system

Claims

1. A property determination method in which a computer executes processes including accepting a request for determination of the property of a subject, acquiring measurement data on the amount of a substance to be measured in a sample provided by the subject, storing the acquired measurement data in a memory unit, making a determination of the property using the measurement data stored in the memory unit, and outputting the determination result, wherein, when a request for determination of the property of the same subject is received at a second time point later than the first time point, with the measurement data corresponding to the request accepted at the first time point stored in the memory unit, the determination of the property is made using the measurement data at the first time point stored in the memory unit.

2. A property determination method as described in claim 1, which includes accepting a request for determination regarding a first property at the first point in time, and acquiring and storing the measurement data in the memory unit; accepting a request for determination regarding a second property at the second point in time; and making a determination regarding the second property using the measurement data at the first point in time stored in the memory unit.

3. The property determination method according to claim 1, wherein the measurement data acquired at the first time point is associated with time information indicating the first time point and stored in the memory unit; at the second time point, a request for determination regarding the property is accepted, and the measurement data acquired at the second time point is associated with time information indicating the second time point and stored in the memory unit; and using the measurement data at the first time point and the measurement data at the second time point stored in the memory unit, a determination regarding the property at the first time point and the second time point is made, and a determination result is output.

4. A property determination method according to any one of claims 1 to 3, wherein the measurement data is the expression level of each of a plurality of small RNAs.

5. The property determination method according to claim 4, wherein the process of acquiring the measurement data is performed using a next-generation sequencer.

6. A property determination method according to any one of claims 1 to 3, wherein the process of determining the property is performed using a machine learning model that has been pre-trained to determine the correspondence between measurement data and determination results.

7. A property determination device comprising: a reception unit that receives a request for determination regarding the property of a subject; an acquisition unit that acquires measurement data regarding the amount of a substance to be measured in a sample provided by the subject and stores the acquired measurement data in a memory unit; and a determination unit that makes a determination regarding the property using the measurement data stored in the memory unit and outputs a determination result, wherein, when the reception unit receives a request for determination regarding the property for the same subject at a second time point that is later in time than the first time point, while the measurement data corresponding to the request received at the first time point is stored in the memory unit, the determination unit makes a determination regarding the property using the measurement data at the first time point stored in the memory unit.

8. A property determination program for causing a computer to function as: a reception unit that receives a request for a determination regarding the property of a subject; an acquisition unit that acquires measurement data regarding the amount of a substance to be measured in a sample provided by the subject and stores the acquired measurement data in a memory unit; and a determination unit that uses the measurement data stored in the memory unit to make a determination regarding the property and output a determination result, wherein when the reception unit receives a request for a determination regarding the property for the same subject at a second time point that is later in time than the first time point, while the measurement data corresponding to the request received at the first time point is stored in the memory unit, the determination unit makes a determination regarding the property using the measurement data at the first time point stored in the memory unit.

9. A property determination system including: a reception unit that receives a request for determination regarding the property of a subject; an acquisition unit that acquires measurement data regarding the amount of a substance to be measured in a sample provided by the subject; a memory unit that stores the acquired measurement data; and a determination unit that makes a determination regarding the property using the measurement data stored in the memory unit and outputs a determination result, wherein, when the reception unit receives a request for determination regarding the property for the same subject at a second time point that is later in time than the first time point, while the measurement data corresponding to the request received at the first time point is stored in the memory unit, the determination unit makes a determination regarding the property using the measurement data at the first time point stored in the memory unit.

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